



'''simple docstring'''



import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device


lowerCAmelCase_  :							List[str]             =    False
class 						lowerCamelCase_				(       unittest.TestCase      ):
						pass


@slow
@require_torch_gpu
class 						lowerCamelCase_				(       unittest.TestCase      ):







						def        __lowercase     (	self :   List[str]					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   List[str]         =      VersatileDiffusionImageVariationPipeline.from_pretrained('''shi-labs/versatile-diffusion'''					)
													pipe.to(lowerCAmelCase__					)
													pipe.set_progress_bar_config(disable=lowerCAmelCase__					)

													SCREAMING_SNAKE_CASE       :   List[str]         =      load_image(
													    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'''					)
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      torch.manual_seed(0					)
													SCREAMING_SNAKE_CASE       :   List[str]         =      pipe(
													    image=lowerCAmelCase__					,     generator=lowerCAmelCase__					,     guidance_scale=7.5					,     num_inference_steps=50					,     output_type='''numpy'''					,     ).images

													SCREAMING_SNAKE_CASE       :   Dict         =      image[0, 2_53:2_56, 2_53:2_56, -1]

													assert image.shape == (1, 5_12, 5_12, 3)
													SCREAMING_SNAKE_CASE       :   Dict         =      np.array([0.0441, 0.0469, 0.0507, 0.0575, 0.0632, 0.0650, 0.0865, 0.0909, 0.0945]					)

													assert np.abs(image_slice.flatten() - expected_slice					).max() < 1e-2









'''simple docstring'''



from collections import defaultdict
def        UpperCAmelCase (    A	:					int					):
							SCREAMING_SNAKE_CASE       :   List[Any]         =      1
							SCREAMING_SNAKE_CASE       :   Dict         =      True
							for v in tree[start]:
														if v not in visited:
																					ret += dfs(A					)
							if ret % 2 == 0:
														cuts.append(A					)
							return ret
def        UpperCAmelCase (    ):
							dfs(1					)


if __name__ == "__main__":
							lowerCAmelCase_      ,				lowerCAmelCase_  :							Dict             =    10, 9
							lowerCAmelCase_  :							Dict             =    defaultdict(list)
							lowerCAmelCase_  :							dict[int, bool]             =    {}
							lowerCAmelCase_  :							list[int]             =    []
							lowerCAmelCase_  :							Optional[Any]             =    0
							lowerCAmelCase_  :							Dict             =    [(2, 1), (3, 1), (4, 3), (5, 2), (6, 1), (7, 2), (8, 6), (9, 8), (10, 8)]
							for u, v in edges:
														tree[u].append(v)
														tree[v].append(u)
							even_tree()
							print(len(cuts) - 1)




